Jelle Zijlstra <jelle.zijls...@gmail.com> added the comment:
I made a similar suggestion in issue46821 (thanks Alex for pointing me to this older issue): Currently, the implementation of @overload (https://github.com/python/cpython/blob/59585d6b2ea50d7bc3a9b336da5bde61367f527c/Lib/typing.py#L2211) simply returns a dummy function and throws away the decorated function. This makes it virtually impossible for type checkers using the runtime function object to find overloads specified at runtime. In pyanalyze, I worked around this by providing a custom @overload decorator, working something like this: _overloads: dict[str, list[Callable]] = {} def _get_key(func: Callable) -> str: return f"{func.__module__}.{func.__qualname__}" def overload(func): key = _get_key(func) _overloads.setdefault(key, []).append(func) return _overload_dummy def get_overloads_for(func): key = _get_key(func) return _overloads.get(key, []) A full implementation will need more error handling. I'd like to add something like this to typing.py so that other tools can also use this information. --- With my suggested solution, help() would need to call typing.get_overloads_for() to get any overloads for the function. Unlike Raymond's suggestion, we would not need to change the function creation machinery. ---------- nosy: +Jelle Zijlstra _______________________________________ Python tracker <rep...@bugs.python.org> <https://bugs.python.org/issue45100> _______________________________________ _______________________________________________ Python-bugs-list mailing list Unsubscribe: https://mail.python.org/mailman/options/python-bugs-list/archive%40mail-archive.com
